Hanhan Zhou

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 18

Top Topics

Policy Gradient

Multi Agent Learning

Reinforcement Learning

Regret Minimization

Top Venues

IEEE Trans. Emerg. Top. Comput. Intell.

Publications

Huiqun Li, Hanhan Zhou, Yifei Zou, Dongxiao Yu, Tian Lan
ConcaveQ: Non-monotonic Value Function Factorization via Concave Representations in Deep Multi-Agent Reinforcement Learning. AAAI (2024)
Zuyuan Zhang, Hanhan Zhou, Mahdi Imani, Taeyoung Lee, Tian Lan
Collaborative AI Teaming in Unknown Environments via Active Goal Deduction. CoRR (2024)
Yongsheng Mei, Hanhan Zhou, Tian Lan
Projection-Optimal Monotonic Value Function Factorization in Multi-Agent Reinforcement Learning. AAMAS (2024)
Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina C. Adam, Nathaniel D. Bastian, Tian Lan
Real-time Network Intrusion Detection via Decision Transformers. CoRR (2023)
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Value Functions Factorization With Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients. IEEE Trans. Emerg. Top. Comput. Intell. 7 (5) (2023)
Huiqun Li, Hanhan Zhou, Yifei Zou, Dongxiao Yu, Tian Lan
ConcaveQ: Non-Monotonic Value Function Factorization via Concave Representations in Deep Multi-Agent Reinforcement Learning. CoRR (2023)
Chang-Lin Chen, Hanhan Zhou, Jiayu Chen, Mohammad Pedramfar, Vaneet Aggarwal, Tian Lan, Zheqing Zhu, Chi Zhou, Tim Gasser, Pol Mauri Ruiz, Vijay Menon, Neeraj Kumar, Hongbo Dong
Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning. CoRR (2023)
Yongsheng Mei, Hanhan Zhou, Tian Lan, Guru Venkataramani, Peng Wei
MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization. AAMAS (2023)
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Statistically Efficient Variance Reduction with Double Policy Estimation for Off-Policy Evaluation in Sequence-Modeled Reinforcement Learning. CoRR (2023)
Hanhan Zhou, Tian Lan, Guru Venkataramani, Wenbo Ding
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction. CoRR (2023)
Yongsheng Mei, Hanhan Zhou, Tian Lan, Guru Venkataramani, Peng Wei
MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization. CoRR (2023)
Hanhan Zhou, Tian Lan, Guru Venkataramani, Wenbo Ding
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction. NeurIPS (2023)
Yongsheng Mei, Hanhan Zhou, Tian Lan
ReMIX: Regret Minimization for Monotonic Value Function Factorization in Multiagent Reinforcement Learning. CoRR (2023)
Hanhan Zhou, Tian Lan, Guru Venkataramani, Wenbo Ding
On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning. CoRR (2022)
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients. CoRR (2022)
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
PAC: Assisted Value Factorization with Counterfactual Predictions in Multi-Agent Reinforcement Learning. NeurIPS (2022)
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning. CoRR (2022)
Hanhan Zhou, Tian Lan, Guru Venkataramani
PT-VTON: an Image-Based Virtual Try-On Network with Progressive Pose Attention Transfer. CoRR (2021)